The suite of course options are designed for ICT professionals who wish to develop skills to support careers in Data Science, Data Engineering. Specialist study areas include big data programming, machine learning, data analytics, AI, Data Programming and Visualisation, Python, R Studio and much more.
Listen to the UCD faculty Dr. Michael Salter Townshend explaining digital transformation in Data Science and future of learning for professionals and how the Advance Centre is addressing the digital skills needs. "Data Science is a very modern term, and it refers mainly to analytics conducted post digital transformation.The digital transformation is ongoing as more industries adopt and embrace data-driven decision making. It is an ever-evolving field, at the very forefront of the digital revolution".
The Data Science covers areas such as big data programming, machine learning, data analytics, AI, Data Programming and Visualisation, Python, R Studio and much more.
delivered by UCD, ATU Sligo and TU Dublin
The suite of course options are designed for ICT professionals who wish to develop skills to support careers in Data Science, Data Engineering. Specialist study areas include big data programming, machine learning, data analytics, AI, Data Programming and Visualisation, Python, R Studio and much more.
This cert has been developed in collaboration with industry and is aimed at Electronic, Computer, Mechanical and Mechatronic Engineers who wish to develop the skills required to design the next generation of technology for smart and autonomous vehicles.
This Postgraduate Certificate specialises in Environment Detection and Computer Vision for Advanced Driver Assistance Systems, the underlaying technology of smart and autonomous vehicles.
Introduction to probability and statistical inference, focusing on understanding concepts and methodologies.
Begineers introduction to the open-source statistical programming language R, and how to build programmes and handle datasets
The part-time online MSc in Data Science offered by ATU Sligo prepares graduates for future work opportunities in data analytics, big data and artificial intelligence.
Learn how to manipulate data and perform statistical analysis using Python.
The micro-credential uses a variety of real-world examples to illustrate the use of different data analytical techniques and regression models, covering both theoretical and practical considerations.
Learn about machine learning, Deep Learning and Convolutional Neural Networks for use in computer vision tasks
This module covers statistical methods to analyse and quantify processes. It will enable learners to model problems using probabilistic and statistical mathematical methods.
Introduces students to “Automotive System Safety and Cybersecurity” and concepts relevant for Advanced Driver Assistance Systems and Self Driving Cars.
Introduces key 2D-Image Processing, segmentation and features detection techniques, camera intrinsic and extrinsic parameters and multiple view geometries.
Introduction to computationally intensive modern Statistical methods, including concepts and methods involved in simulating from distributions using R.
Gain expertise in interpreting linear algebra models used in the engineering literature to model problems
This module involves modelling and analysis of vehicle dynamics including drag, tyre friction and vibration and the effect of these on the vehicle performance and driver experience.
ADAS provides the learner with an appreciation for the bigger picture of the automotive industry. The student will gain an understanding of the multi-disciplinary nature of the industry.
This topic will introduce the learner to the SOTA data analysis tools and techniques, which help to interpret and extract meaningful information from data (using public datasets).
This module investigates the physical and technical foundations, strengths and weaknesses of sensors for advanced driver assistance systems and their applications in environment detection in automotive vehicles
This micro-credential delivers a collection of techniques for discovering patterns in data and making predictions at the intersection of Machine Learning and Statistics.
This micro-credential delivers the basic techniques in Time Series Analysis. This course will mainly focus on examples in the world of economics and finance.
This micro-credential will provide an introduction to Bayesian analysis with an emphasis on concepts in Bayesian theory and practice, focusing on statistical programming (Stan programming language).
This micro-credential will cover many common statistical techniques used to analyse high dimensional data (including: clustering techniques; classification techniques; ordination techniques; etc) using R software.
Covers the essence of programming with data using the languages C and C++, focus on incorporating such code into the R statistical environment.
Focuses on how to manipulate data and perform statistical calculations using SAS.
Covers advanced use of R and Rstudio, following on from the Data Programming with R module.
Focuses on the analysis of relational data and reviews the available methodologies and algorithms that can be employed to model network interactions.
An introductory course in C programming for the PC. Covering the C compiler, variables, operators, decision statements, iteration loops, arrays and strings
The Programme in Data Analytics is at the crossroads between statistics and computer science, and contain elements of both. Students who perform well on the Professional Diploma may apply to transfer to online MSc Data Analytics.
The Programme in Data Analytics will equip you with the skills necessary to understand and analyse large data sets. Techniquies applicable to ICT, pharma and financial services sectors amongst others.
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Learn from 3 of Ireland’s leading universities with world renowned academic staff.
Our courses and modules range from levels 6 to 9 on the NFQ framework.
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Select from 11 key themes across Digital Transformation.
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Our corporate network is innovative and expansive across many sectors.
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Choose from a range of online, on-campus and blended learning modes designed to suit your needs.
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